We consider the problem of embedding entities and relationships of multi-relational data in low-dimensional vector spaces.
#11 best model for Link Prediction on WN18RR
Motivated by this example, we present a simple method for finding phrases in text, and show that learning good vector representations for millions of phrases is possible.
This paper presents a novel algorithm, based upon the dependent Dirichlet process mixture model (DDPMM), for clustering batch-sequential data containing an unknown number of evolving clusters.
Shannon's entropy is a basic quantity in information theory, and a fundamental building block for the analysis of neural codes.
Given a convergent sequence of graphs, there exists a limit object called the graphon from which random graphs are generated.
Recent work has shown how denoising and contractive autoencoders implicitly capture the structure of the data-generating density, in the case where the corruption noise is Gaussian, the reconstruction error is the squared error, and the data is continuous-valued.